Search results for " processing"

2020

Recommender systems are information software that retrieves relevant items for users from massive sources of data. The variational autoencoder (VAE) has proven to be a promising approach for recommendation systems, as it can explore high-level user-item relations and extract contingencies from the input effectively. However, the previous variants of VAE have so far seen limited application to domain-specific recommendations that require additional side information. Hence, The Ensemble Variational Autoencoder framework for recommendations (EnsVAE) is proposed. This architecture specifies a procedure to transform sub-recommenders’ predicted utility matrix into interest probabilities that allo…

A platform for the development and the validation of HW IP components starting from reference software specifications

2008

Abstract Signal processing algorithms become more and more efficient as a result of the developments of new standards. It is particularly true in the field video compression. However, at each improvement in efficiency and functionality, the complexity of the algorithms is also increasing. Textual specifications, that in the past were the original form of specifications, have been substituted by reference software which became the starting point of any design flow leading to implementation. Therefore, designing an embedded application has become equivalent to port a generic software on a, possibly heterogeneous, embedded platform. Such operation is getting more and more difficult because of …

State of the Art in Information Security Policy Development

2020

Despite the prevalence of research that exists under the label of “information security policies” (ISPs), there is no consensus on what an ISP means or how ISPs should be developed. This article reviews state-of-the-art ISP development by examining a diverse sample of literature on the subject. The definition and function of an ISP is studied first, revealing a rich tapestry of different notions behind the same term. When looking at the broad picture of the research on ISP development methods, we find different phases and levels of detail. Analyzing the different views on the content, context, and strategy alignment provides for further understanding on the complexity of the matter. As an o…

Assessing the Performance of Interactive Multiobjective Optimization Methods

2021

Interactive methods are useful decision-making tools for multiobjective optimization problems, because they allow a decision-maker to provide her/his preference information iteratively in a comfortable way at the same time as (s)he learns about all different aspects of the problem. A wide variety of interactive methods is nowadays available, and they differ from each other in both technical aspects and type of preference information employed. Therefore, assessing the performance of interactive methods can help users to choose the most appropriate one for a given problem. This is a challenging task, which has been tackled from different perspectives in the published literature. We present a …

The potential of temporal analysis: Combining log data and lag sequential analysis to investigate temporal differences between scaffolded and non-sca…

2020

This paper contributes to the ongoing discussion about analysing the temporal aspects of learning processes in the educational technology research field. Our main aim was to advance methods for analysing temporal aspects of technology-enhanced learning (TEL) processes by introducing the temporal lag sequential analysis (TLSA) technique and by combining TLSA with temporal log data analysis (TLDA). Our secondary aim was to illustrate the potential of these two analysis techniques to reveal the differences between the face-to-face technology-enhanced collaborative inquiry-based learning (CIBL) processes of three different conditions (non-scaffolded, writing scaffolded and script scaffolded gro…

HyperLabelMe : A Web Platform for Benchmarking Remote-Sensing Image Classifiers

2017

HyperLabelMe is a web platform that allows the automatic benchmarking of remote-sensing image classifiers. To demonstrate this platform's attributes, we collected and harmonized a large data set of labeled multispectral and hyperspectral images with different numbers of classes, dimensionality, noise sources, and levels. The registered user can download training data pairs (spectra and land cover/use labels) and submit the predictions for unseen testing spectra. The system then evaluates the accuracy and robustness of the classifier, and it reports different scores as well as a ranked list of the best methods and users. The system is modular, scalable, and ever-growing in data sets and clas…

Higher-Fidelity Frugal and Accurate Quantile Estimation Using a Novel Incremental <italic>Discretized</italic> Paradigm

2018

Traditional pattern classification works with the moments of the distributions of the features and involves the estimation of the means and variances. As opposed to this, more recently, research has indicated the power of using the quantiles of the distributions because they are more robust and applicable for non-parametric methods. The estimation of the quantiles is even more pertinent when one is mining data streams. However, the complexity of quantile estimation is much higher than the corresponding estimation of the mean and variance, and this increased complexity is more relevant as the size of the data increases. Clearly, in the context of infinite data streams, a computational and sp…

Exact results for accepting probabilities of quantum automata

2001

One of the properties of Kondacs-Watrous model of quantum finite automata (QFA) is that the probability of the correct answer for a QFA cannot be amplified arbitrarily. In this paper, we determine the maximum probabilities achieved by QFAs for several languages. In particular, we show that any language that is not recognized by an RFA (reversible finite automaton) can be recognized by a QFA with probability at most 0.7726...

Word assembly through minimal forbidden words

2006

AbstractWe give a linear-time algorithm to reconstruct a finite word w over a finite alphabet A of constant size starting from a finite set of factors of w verifying a suitable hypothesis. We use combinatorics techniques based on the minimal forbidden words, which have been introduced in previous papers. This improves a previous algorithm which worked under the assumption of stronger hypothesis.

Using skeleton and Hough transform variant to correct skew in historical documents

2020

International audience; As a main part of several document analysis systems, Skew estimation represents one of the major research challenges, particularly in case of historical documents exploration. In this paper, we propose an original skew angle detection and correction technique. Morphological Skeleton is introduced to considerably diminish the amount of data by eliminating the redundant pixels and preserving only the central curves of the image components. Next, the proposed method uses Progressive Probabilistic Hough Transform (PPHT) to find image lines. At the end, a specific procedure is applied in order to measure the global skew angle of the document image from these identified li…